Cut a numeric variable into groups (bins) with advanced options

Usage

adv_cut(
  x,
  ncuts = NULL,
  eq_groups = FALSE,
  cuts = NULL,
  num_labels = FALSE,
  labels = NULL,
  include_oob = TRUE,
  labels_at_means = TRUE,
  label_pairs_format = "[%.2f, %.2f]",
  ...
)

Arguments

x

vector of numeric values to cut into groups

ncuts

number of cuts (default: NULL)

eq_groups

should the groups be equal (default: FALSE)

cuts

where to put the cuts (default: NULL), not used if ncuts is used

num_labels

should the labels be transformed into numbers (default: FALSE)

labels

a vector of labels to use for the groups (default: NULL)

include_oob

include values outside of the boundaries provided in cuts (default: TRUE)

labels_at_means

should labels be created as means between cuts (TRUE) or as pairs of cuts (FALSE)

label_pairs_format

formatting string to use when labels are generated from pairs of cuts (default: [%.2f, %.2f])

...

other parameters passed to base::cut

If ncuts is used, then the variable is cut into N cuts either of equal group size (eq_groups = TRUE) or equally distant from each other (eq_groups = FALSE). If labels are not provided, they are generated as means between cuts if labels_at_means is TRUE.

Value

A factor assigning each element of x to a bin, or a numeric vector of bin labels when num_labels = TRUE. The result has the same length as x.

Examples

set.seed(1)
x <- sample(1:100, 20)
sort(x)
#>  [1]  1  7 14 21 34 37 39 43 51 54 59 68 73 74 79 82 83 85 87 97

adv_cut(x, ncuts = 5)
#>  [1] 68.2 29.8 10.6 29.8 87.4 49   10.6 87.4 68.2 49   87.4 29.8 49   68.2 10.6
#> [16] 68.2 87.4 29.8 87.4 87.4
#> Levels: 10.6 29.8 49 68.2 87.4
adv_cut(x, ncuts = 5, eq_groups = TRUE)
#>  [1] 62   42.5 17.5 17.5 90   42.5 17.5 78   62   42.5 90   17.5 62   78   17.5
#> [16] 62   78   42.5 78   90  
#> Levels: 17.5 42.5 62 78 90
adv_cut(x, ncuts = 5, eq_groups = TRUE, num_labels = TRUE)
#>  [1] 62.0 42.5 17.5 17.5 90.0 42.5 17.5 78.0 62.0 42.5 90.0 17.5 62.0 78.0 17.5
#> [16] 62.0 78.0 42.5 78.0 90.0
adv_cut(x, ncuts = 5, eq_groups = TRUE, labels_at_means = FALSE)
#>  [1] [51.00, 73.00] [34.00, 51.00] [1.00, 34.00]  [1.00, 34.00]  [83.00, 97.00]
#>  [6] [34.00, 51.00] [1.00, 34.00]  [73.00, 83.00] [51.00, 73.00] [34.00, 51.00]
#> [11] [83.00, 97.00] [1.00, 34.00]  [51.00, 73.00] [73.00, 83.00] [1.00, 34.00] 
#> [16] [51.00, 73.00] [73.00, 83.00] [34.00, 51.00] [73.00, 83.00] [83.00, 97.00]
#> 5 Levels: [1.00, 34.00] [34.00, 51.00] [51.00, 73.00] ... [83.00, 97.00]
adv_cut(x, cuts = seq(0, 100, by = 20))
#>  [1] 70 30 10 30 90 50 10 90 50 50 90 30 50 70 10 70 70 30 90 90
#> Levels: 10 30 50 70 90
adv_cut(x, cuts = seq(0, 100, by = 20), labels_at_means = FALSE)
#>  [1] [60.00, 80.00]  [20.00, 40.00]  [0.00, 20.00]   [20.00, 40.00] 
#>  [5] [80.00, 100.00] [40.00, 60.00]  [0.00, 20.00]   [80.00, 100.00]
#>  [9] [40.00, 60.00]  [40.00, 60.00]  [80.00, 100.00] [20.00, 40.00] 
#> [13] [40.00, 60.00]  [60.00, 80.00]  [0.00, 20.00]   [60.00, 80.00] 
#> [17] [60.00, 80.00]  [20.00, 40.00]  [80.00, 100.00] [80.00, 100.00]
#> 5 Levels: [0.00, 20.00] [20.00, 40.00] [40.00, 60.00] ... [80.00, 100.00]
adv_cut(x, cuts = seq(0, 100, by = 20), 
           labels_at_means = FALSE, label_pairs_format = "[%i, %i]")
#>  [1] [60, 80]  [20, 40]  [0, 20]   [20, 40]  [80, 100] [40, 60]  [0, 20]  
#>  [8] [80, 100] [40, 60]  [40, 60]  [80, 100] [20, 40]  [40, 60]  [60, 80] 
#> [15] [0, 20]   [60, 80]  [60, 80]  [20, 40]  [80, 100] [80, 100]
#> Levels: [0, 20] [20, 40] [40, 60] [60, 80] [80, 100]